CN103827697A - Method and apparatus for sorting lidar data - Google Patents

Abstract

A programmed computer or non-transitory computer readable storage media has instructions that are executable by a processor to identify LiDAR data points associated with items of vegetation or other objects. Each LiDAR data point is tested to determine if it lies within the value of a closed surface defined for higher LiDAR points. If so, the LiDAR point is grouped with the LiDAR points associated with a previously identified item of vegetation. If not, a new item of vegetation is identified.

Description

For the method and apparatus of the LiDAR data of classifying

The application is authorized to and requires in the non-temporary patent application No.13/245 of U.S. submission on September 26th, 2011 and " Method and Apparatus for Sorting LiDar Data " by name, 514 benefit of priority, its content is comprised in this by reference.

Technical field

Technology disclosed herein relates to remote sensing and relates to particularly the system for LiDAR data point being divided into groups to identify vegetation item.

Background technology

As substituting of the inspection physically of the area-of-interest for such as forest tract (forest tract) etc., many land owners assist forest management by remote sensing technology.Such remote sensing technology can be used for estimating the quantity of the trees in interested region and assessing its average height, the age of tree, marketable value and other information.A widely used remote sensing technology is light detection and ranging (LiDAR).Use LiDAR, aircraft above area-of-interest flight and aircraft on transmission and sensing cell by laser pulse directed towards ground.Receive from the detected unit of laser pulse of vegetation and/or ground return.Because the speed of aircraft and be highly known, so provide the three-dimensional coordinate for the pulse of each reflection the two-way time of each pulse.Coordinate can be combined to produce the topomap of area-of-interest in computing machine.

A problem analyzing LiDAR data is to determine which LiDAR data point is associated with independent trees in area-of-interest or other vegetation item.For this reason, a technology is in U.S. Patent No. 7,474, and in 964 open (" ' 964 "), this patent is comprised in this by reference.In ' 964 patents, define digital umbrella for LiDAR point.Those LiDAR points that are positioned at the overlapping digital umbrella region of higher point are assumed to be with identical vegetation item and are associated.Although the technology of describing in ' 964 patents works well, can improve for the independent vegetation item of for example trees in area-of-interest or other objects.

Accompanying drawing explanation

Figure 1A and Figure 1B illustrate the known technology for LiDAR data point is divided into groups;

Fig. 2 A and Fig. 2 B illustrate the technology for LiDAR point is divided into groups according to disclosed technology embodiment;

Fig. 3 illustrates an embodiment of the computer system for implementing disclosed technology;

Fig. 4 illustrates curve map, and how described curve map shows one group of LiDAR data point from area-of-interest by highly classifying;

Fig. 5 illustrates for determining whether adjacent LiDAR data point belongs to a technology of the identical group that is associated from independent vegetation item or different group;

Fig. 6 is the process flow diagram of carrying out the step LiDAR data point is divided into groups according to disclosed technology embodiment by computer system;

Fig. 7 illustrates the whether crossing method of LiDAR point being associated with two spheroids of determining.

Embodiment

As being described in further detail hereinafter, technology disclosed herein relates to the method for LiDAR data point being divided into groups to identify vegetation item or other objects.In one embodiment, LiDAR data point is associated with the volume defining by confining surface.Those LiDAR data points that intersect with their volumes are grouped or are associated with independent vegetation item.Those LiDAR points without crossing volume are associated from different vegetation items.In one embodiment, the confining surface that has defined volume is spheroid.In other embodiments, confining surface for example depends on that just the character shape in analyzed vegetation can be the three-dimensional surface of spheroid, cylinder, cone or other sealings.

Figure 1A and Figure 1B illustrate a known method LiDAR data point being divided into groups to identify vegetation item.As hereinbefore, in US Patent No 7,474, described in 964, LiDAR data point 50,54,56 has for example represented, from the reflection of the first vegetation item (, trees) 60, and the reflection that LiDAR data point 64 and 66 represents from the second trees 70.For the quantity of the trees in zoning, numeral hat umbrella is associated with each in LiDAR data point 50,54,56.The size of each umbrella depends on the height of laser pulse and the feature of the tree type that is dominant in analyzed region of reflection.Any LiDAR data point that is positioned at the digital umbrella below of any these restrictions is classified as the vegetation item that belongs to identical.Better for lacking, the group of the collection of LiDAR data point bunch is often called as " piece ".As visible in Figure 1A, LiDAR data point 64,66 is positioned at the digital umbrella below being associated with LiDAR point 54.Therefore, these LiDAR data points may be assumed to be mistakenly in identical piece, although they are associated with the second trees.By the part using any LiDAR data point grouping of umbrella below as identical piece, the quantity of the trees in given area-of-interest may be underestimated.

In order to improve the technology of describing in ' 964 patents, disclosed technical operation is to limit the confining surface around each LiDAR data point.Confining surface can be avette (for example, spheroid), spheroid, cylinder, cone or other shapes.Specific shape can be depending on the natural shape of vegetation sensed in area-of-interest, or can produce the statistics of accurate result based on which shape and select.Confining surface shape can be symmetry or asymmetrical.In alternative embodiment, different confining surfaces can be for for example limiting for the spheroid of higher point with for the LiDAR point of the spheroid of lower point.For object of the present disclosure, it is spheroid that confining surface is described to.But, the disclosed technology of recognizing is also applied to other shapes.

As visible in Fig. 2 A, LiDAR data point 80,82,84 generates by the reflection quilt from independent trees 90.Each LiDAR data point is associated with corresponding spheroid 80e, 82e, 84e.In one embodiment, the size of spheroid depends on the height of corresponding LiDAR data point.Those higher LiDAR data points have corresponding larger spheroid, and apart from ground, those lower LiDAR data points have corresponding less spheroid on the contrary.

In one embodiment, spheroid not centered by LiDAR data point but moved apart from dZ, describedly depends on apart from dZ the height that LiDAR is ordered.In one embodiment, be confirmed as dZ=max (R apart from dZ _i* C _o-C _o, O), wherein R _ithe radius of the selected spheroid of statistical study of the ground truth of the seeds based on interested, and C _obe statistical items, described statistical items is selected such that each almost exists trees.As initial estimation, by C _ovalue be selected as 0.1.The initial radium of spheroid and extension thereof and C _oend value in optimizing process, determine, the parameter that each of described optimizing process inquiry identified how many trees and then adjusted spheroid makes the trees quantity of every approach 1.

Fig. 2 A also shows the LiDAR data point 94,96 being associated with the second trees 100.LiDAR data point 94,96 is associated with corresponding spheroid 94e and 96e.In order to determine whether LiDAR data point belongs to independent vegetation item or multiple vegetation item, computer system is determined that whether any of the spheroid that is associated with each LiDAR data point be crossing or is dropped in the volume of another spheroid.If so, LiDAR data point is together with being grouped in independent piece that independent vegetation item is associated.If the spheroid of LiDAR data point is not in the volume of previously defined spheroid, computer system is determined and in LiDAR data, has been found new vegetation item and limited new piece for this vegetation item.In the example shown in Fig. 2 A, the spheroid 96e being associated with LiDAR data point 96 is positioned at the volume of the spheroid 94e being associated with LiDAR data point 94.Therefore, LiDAR data point 94 is grouped in together in the identical piece of having identified the vegetation item that separates or trees 100 with 96.

As visible in Fig. 2 B, in the time looking down in LiDAR data point, LiDAR data point 80,82,84 is grouped in first, and LiDAR data point 94,96 is grouped in second, to identify the vegetation item of separation.By contrast, as shown at Figure 1A, LiDAR data point 50,54,56,64,66 is grouped in the independent piece that only defines corresponding independent vegetation item.

Fig. 3 illustrates the representational computer system that can be used for implementing disclosed technology.Computer system 200 comprises the one or more programmable processor (not shown) that are configured to carry out programmed instruction on the non-volatile computer readable media 202 that is stored in for example CD, DVD, hard disk drive, flash drive or that receive from remote source via the compunication link of for example internet 204.

Computer system operation is with execution of program instructions, so as by LiDAR Data classification be representative independent or at a distance of the piece of vegetation item closely.The group of LiDAR data can be combined to figure, and described figure can show and maybe can use printer 212 to be printed on physical medium on display 210.Alternatively, the group of data can be stored in the Computer Storage of for example database 220, for observation and analysis subsequently.Alternatively, the group of LiDAR data can be delivered to one or more computer systems at a distance that are positioned at via compunication link, for observing or analyzing.

In one embodiment, by the classification for the first time for LiDAR data point, by LiDAR data point be grouped into represent independent or at a distance of the piece of vegetation item closely.As shown in FIG. 4, the area-of-interest 230 of for example forest can be patrolled and is associated with millions of LiDAR data points.LiDAR data point is stored in computer-readable medium and receives by computer system 200, described computer system 200 analyze data point with limit represent independent or at a distance of vegetation item closely.In order to accelerate to process, area-of-interest can be divided into less subregion, for example region 234, described subregion 234 is for example 20 × 20 or 30 × 30 square metres.But, should be appreciated that and depend on that the processing power of related computer system and storer can use other size.

In one embodiment, each LiDAR data point and x, y and z coordinates correlation connection, wherein z has represented the sea level elevation of the LiDAR pulse of reflection.First LiDAR data point is classified according to its sea level elevation, and described classification starts with the peak in the group of LiDAR data point that will be analyzed, as shown in FIG. 4.In one embodiment, suppose that the highest LiDAR data point in group is associated with the top of trees or other independent vegetation items.Remaining LiDAR data point in group is analyzed to determine whether they are in the border of confining surface of the LiDAR data point restriction in the group with higher height above sea level.

Fig. 5 illustrates the LiDAR data point 250 that the reflection at the top of origin trees 252 causes.Define spheroid 254 for LiDAR data point 250.Spheroid 254 has the size limiting by its minor axis and major axis, and described minor axis and major axis depend on the height of LiDAR point 250.The statistical study of the specific interested geographic area that the relation between the size of the height that LiDAR is ordered and the spheroid causing can be based on for being taken or the ground truth of vegetation type is selected.For example, some trees may be high and with little bizet, for example pesudotsuga taxifolia, and other trees may have wider bizet, such as Deciduous tree etc.In addition, the size of the spheroid causing may depend on other factors, the sealing degree of for example interested forest.The canopy with larger sealing degree typically comprises the trees with less bizet.Estimate that the method for sealing degree of the area-of-interest of patrolling by LiDAR data is at disclosed U.S. Patent application No.12/645,348(" ' 348 ") in describe, it is comprised in this by reference.

Once spheroid forms, the other LiDAR point in data group and the volume surrounding by spheroid are contrasted.In the example shown, identified LiDAR point 260.For determining whether LiDAR point 260 represents new trees or a part for the trees that are associated with LiDAR point 250, and computer system determines whether the coordinate of LiDAR point 260 is in the border of spheroid 254.In one embodiment, whether computer system is located at by calculating the x of LiDAR point 260 and y coordinate that the radius R 2 of the spheroid 254 that the At The Height of LiDAR point 260 obtains is interior to be determined this.If x and y coordinate are positioned at radius R 2, LiDAR point 260 is included in the identical piece limiting for LiDAR point 250.If x and y coordinate are not in radius R 2, LiDAR point 260 can limit the new piece being associated with another vegetation item of for example trees 270.

As recognized, exist and can be used for determining whether LiDAR point should be included in identical piece, maybe should be grouped in the other technologies in different pieces.For example, can limit spheroid and computer system for each LiDAR point and can determine the whether overlapping or contact in the surface of spheroid.If so any LiDAR data point, being associated with contact or overlapping spheroid is included in identical piece.

If use for the accurate geometric formula of spheroid and carry out algebraically from equation and calculate described intersecting, determine that whether two spheroids intersect is to calculate upper complex calculations.The object of the collection of ordering for LiDAR in one embodiment, bunch does not need accurately.In the time of known following situation, method as described below intersects very approximate for test:

1) initial point of the first spheroid has the Z value larger than the second spheroid (, highly).

2) two spheroids are spherical (L=R) or in Z direction, be (L>R) extending.

In the example shown in Fig. 7, suppose that the first spheroid is centered in the world coordinates place of x=0, z=0.The initial point of the second spheroid is (tx, tz).Radius and the length of the first spheroid is designated as (R1, L1).Radius and the length of the second spheroid is designated as (R2, L2).

Whether overlapping for determining spheroid

1) value of calculating t=tx/tz.In geometric terminology, this is the slope of the line of centres of two spheroids of 1/().

2) determine the point on the first spheroid, the slope that is wherein parallel to the line of spheroid equals t.First, use the first order derivative of spheroid equation find necessary x value and solve x, wherein slope=t:

$\mathrm{xt}1=\sqrt{\frac{{R1}^2}{\frac{{L1}^2}{t^2*{R1}^2}+1}}$

And determine corresponding z value:

$\mathrm{zt}1=-\sqrt{({L1}^2*(1-\frac{{\mathrm{xt}1}^2}{{R1}^2}))}$

Similarly, calculate the value of xt2, zt2 for the second spheroid:

$\mathrm{xt}2=\mathrm{tx}-\sqrt{\frac{{R2}^2}{\frac{{L2}^2}{t^2*{R2}^2}+1}}$

$\mathrm{zt}2-\mathrm{tz}+\sqrt{({L2}^2*(1-\frac{{\mathrm{xt}2}^2}{{R2}^2}))}$

If the accurate some place contact of two points on two different spheroids on spheroid, they can be in an accurately position contact.But two spheroids must contact.These two points and the line segment connecting have provided the boundary that can testedly be included in the intermediate point in the first spheroid.

3) next calculate the average weighted intermediate point as two points (xt1, zt1) and (xt2, zt2).If L1/R1>L2/R2, for the weight of second point is:

$w2=.5-.5*\frac{{\left(\frac{\frac{L1}{R1}-\frac{L2}{R2}}{\frac{L1}{R1}+\frac{L2}{R2}}\right)}^2}{t}$

Otherwise

$w2=.5+.5*\frac{{\left(\frac{\frac{L2}{R2}-\frac{L1}{R1}}{\frac{L1}{R1}+\frac{L2}{R2}}\right)}^2}{t}$

4) then calculate the value of w1 by following formula:

w1=1-w2

5) then, calculate the mid point (xm, zm) of weighting by following formula:

xm＝w1*xt1+w2*xt2

zm＝w1*zt1+w2*zt2

6) last, by determining whether the mid point (xm, zm) of testing weighting as lower inequality is comprised in the first spheroid to observe it:

$\frac{{\mathrm{xm}}^2}{{R1}^2}+\frac{{\mathrm{zm}}^2}{{L1}^2}<1$

If inequality is set up, midpoint is in the first spheroid inner side, and the second spheroid is crossing with the first spheroid in most applications.This process on calculating more effectively and therein the second spheroid just in the outside of the first spheroid or just lost some degree of accuracy in the border condition of side therein.Actual loss of accuracy's amount not yet determined, only used a large amount of spheroids that generate randomly on inspection for the visual inspection of the performance of process.

Fig. 6 illustrates a series of according to disclosed technology step that embodiment carries out by computer system, with by with independent or at a distance of vegetation item is associated closely LiDAR data point grouping.

Start at 300 places, computer system obtains or receives the LiDAR data of area-of-interest.At 302 places, LiDAR data are divided into less part or group by computer system, for example, cover the group of 20 × 20 or 30 × 30 square metres.This step can be depending on computing power and storer available in computer system, whether use multiprocessor etc. but optional.At 304 places, computer system is by LiDAR Data classification.In one embodiment, the LiDAR data in group are classified to minimum altitude from maximum height.At 308 places, computer system defines for the spheroid of the highest LiDAR data point in group or other confining surface shapes.According to an embodiment, the highest LiDAR data point defines treetop and other LiDAR data points contrast treetop therewith.

At 310 places, computer system starts circulation, the remaining LiDAR data point in described cycle analysis group.At 312 places, computer system determines that whether LiDAR point is more than left predetermined rice number " T " from all remaining higher points.If so, LiDAR data point is confirmed as new vegetation item and puts for this and limit new piece at 314 places.If " T " is five meters in one embodiment, and three-dimensional distance between LiDAR data point and consecutive point thereof is confirmed as exceeding five meters, and LiDAR data point has been considered to represent new vegetation item.But, it will be appreciated that the statistical study or other factors that can be depending on ground truth are used specific " T " value maybe can adjust specifically " T " value by the user of computer system.

If LiDAR data point is no more than apart from the adjacent predetermined distance of LiDAR data point " T ", computer system determines that at 315 places LiDAR data point is whether in for example, spheroid in (, higher) LiDAR data point of any previous analysis.If so, be endowed nearest piece at the 320 interested LiDAR points in place.

In one embodiment, carry out the most close interested LiDAR point of spheroid calculating to determine which is associated with piece.Can determine hithermost based on distance.The quantity of the spheroid in alternatively, can the piece based on ordering at more close interested LiDAR is determined hithermost.Then process and advance to step 322, wherein determine whether that all LiDAR data points in group all Ce Shi not.If not, turn back to step 310 at 324 places for interested LiDAR point restriction spheroid and processing, for the next LiDAR point in group, as mentioned above.Once in group, all LiDAR points are all analyzed, process at 330 places and finish.

As recognized from the above, disclosed technical operation is grouped into by LiDAR data point the group of vegetation item or the ability of piece of representing to improve computer system.By limiting around the confining surface of each LiDAR data point, can be whether a part for identical piece or represent that the vegetation item separating better determines for lower LiDAR data point.

The embodiment of the theme described in this instructions and operation can with the Fundamental Digital Circuit of disclosed structure in being included in this instructions and equivalent structures thereof computer software, firmware or hardware are implemented or with them in one or more combinations be implemented.The embodiment of the theme of describing in this instructions can be embodied as by executing data treatment facility or control it and operate in one or more computer programs of encoding on computer-readable storage medium, that is, and and one or more modules of computer program instructions.

Computer-readable storage medium can be the memory storage of non-volatile embodied on computer readable, the storage substrate of embodied on computer readable, random or sequential-access memory array or device or their one or more combination, maybe can be included therein.In addition,, although computer-readable storage medium is not the signal of propagating, computer-readable storage medium can be source or the object of the computer program instructions of encoding in the signal of the artificial propagation generating.Computer-readable storage medium can be also one or more physical units that separate or medium (for example multiple CD, dish or other memory storages) or be included therein.The operation of describing in this instructions can be used as the operation of being carried out in the data that are stored in the memory storage of one or more embodied on computer readable or receive from other sources by data processing equipment.

Term " data processing equipment " comprises all types of units for the treatment of data, machine, for example, comprise programmable processor, computing machine, system on chip or the multiple or combination in them.Equipment can comprise dedicated logic circuit, for example FPGA(field programmable gate array) or ASIC(special IC).Except hardware, equipment also can comprise the code of the execution environment of having created described computer program, for example, form the code of processor firmware, protocol stack, data base management system (DBMS), operating system, cross-platform working time environment, virtual machine or their one or more combination.Equipment and execution environment can be realized various computation model framework, for example, and network service, Distributed Calculation and grid computing framework.

Computer program (being also known as program, software, software application, script or code) can be write by programming language in any form, comprise assembly language or interpretative code, declaration formula language or process type language, and can be deployed in any form, comprise as stand-alone program or as module, parts, subroutine, object or other unit that is suitable for using in computing environment.Computer program can but must be corresponding to the file in file system.Program (for example can be stored in the part of the file that has kept other programs or data, be stored in the one or more scripts in marking language document), be exclusively used in the individual files of described program, or for example, in the file of multiple assistance (, storing the file of the part of one or more modules, subroutine or code).Computer program can be deployed to be positioned at that multiple place place is extended across in the three unities place or distribution and to carry out on an interconnected computing machine or multiple computing machine by communication network.

The processing of describing in this instructions and logic flow can be carried out by one or more programmable processors of carrying out one or more computer programs, to carry out effect by operate and generate output in input data.Process and logic flow also can be carried out by equipment and also this equipment can be implemented as special purpose logic circuitry, for example FPGA(field programmable gate array) or ASIC(special IC).

The processor that is suitable for computer program for example comprises general and special microprocessor, and any one or more processors of the digital machine of any type.Usually, processor will be from ROM (read-only memory) or random access storage device or the two reception instruction and data.The crucial element of computing machine is processor for performing an action according to instruction and for storing one or more storage arrangements of instruction and data.Usually, computing machine also by comprise or be operationally coupled to one or more for storing the mass storage device of data, for example disk, magneto-optic disk or CD, with from its receive data or to its transmission data.But computing machine must not have this device.In addition, computing machine can be embedded in another device, for example mobile phone, PDA(Personal Digital Assistant), Mobile audio frequency or video player, game console, GPS (GPS) receiver or portable memory are (for example, USB (universal serial bus) (USB) flash drive), etc.The device that is suitable for storing computer program instructions and data comprises nonvolatile memory, medium and the memory storage of form of ownership, for example comprise semiconductor memory system, for example EPROM, EEPROM and flash memory device, disk (for example internal hard drive or removable dish), magneto-optic disk and CD-ROM dish and DVD-ROM dish.Processor and storer can be added special purpose logic circuitry or be comprised in special purpose logic circuitry.

For mutual with user is provided, the embodiment of the theme of describing in this instructions can be embodied on following computing machine, it has for example LCD(liquid crystal display), LED(light emitting diode) or OLED(Organic Light Emitting Diode) display equipment of monitor, for showing information to user, and there is keyboard and indicating device, for example mouse or trace ball, can be provided to computing machine by input by its user.In some embodiments, touch-screen can be used for demonstration information and receives input from user.The device of other types also can be used for providing mutual with user, and the feedback that is provided to user can be any type of sensor feedback, for example visual feedback, audio feedback or tactile feedback; And can receive with any form that comprises sound, voice or sense of touch input from user's input.In addition, computing machine can by send document to user and from the device that used by user receive document and and user interactions; For example,, by webpage being sent to the web browser user's customer set up in response to the request receiving from web browser.

The embodiment of the theme of describing in this instructions may be implemented in the computing system that comprises back-end component, for example, as data server, or described computing system comprises middleware component, for example application server, or described computing system comprises front end component, for example there is the client computer of graphic user interface or web browser, can be mutual with the embodiment of the theme of describing in this instructions by graphic user interface or web browser user, or described computing system comprises one or more these back-end components, any combination of middleware component or front end component.The parts of system can interconnect by any type of digital data communication of for example communication network or its medium.The example of communication network comprises LAN (Local Area Network) (" LAN ") and wide area network (" WAN "), internet (for example, Internet) and reciprocity internet (for example, ad hoc peer-to-peer network).

Computing system can comprise any amount of client and server.Client and server usually mutually away from and typically by communication network mutually mutual.The relation of client and server is due to computer program operation and mutually have client-server relation and cause on computing machine separately.In certain embodiments, data (, html web page) are sent to customer set up (for example, for to showing data with the mutual user of customer set up or receiving the object of user's input from user) by server for example.The data (for example, the result of customer interaction) that generate at customer set up place can receive from customer set up at server place.

From above, will recognize specific embodiments of the invention in this case purposes of illustration describe, but can carry out multiple modification and not depart from scope of the present invention.For example, although the trees in Technical Reference identification area-of-interest are described, it will be appreciated that disclosed technology can be applicable to other interested objects.Therefore, the present invention is not limited, unless by subsidiary claim and equivalents thereof.

Claims (15)

1. be a computer-implemented method for group by LiDAR Data classification, comprise:

Receive one group of LiDAR data point about area-of-interest;

Analyze each in the LiDAR data point in described group to determine whether LiDAR data point has the position in the confining surface that one or more other LiDAR data points in for described group limit; And

If so, described LiDAR data point is added to the previously defined LiDAR group of data points being associated with object; And

If not, limit the new LiDAR group of data points being associated with new object.

2. method according to claim 1, wherein, described object is the trees in forest.

3. method according to claim 1, wherein, described confining surface is ellipsoid.

4. method according to claim 1, wherein, described confining surface is sphere.

5. method according to claim 1, wherein, described confining surface is the conical surface.

6. method according to claim 1, wherein, described confining surface is cylinder.

7. method according to claim 3, wherein, whether described LiDAR data point carries out in the radius of determining the spheroid whether coordinate by determining analyzed described LiDAR data point obtain at the At The Height of analyzed described LiDAR data point in described confining surface.

8. method according to claim 1, wherein, the described confining surface limiting for each LiDAR data point has the size of the height that depends on described LiDAR data point.

9. method according to claim 2, wherein, the described confining surface limiting for each LiDAR data point has and depends on the size that obtains the sealing degree value of described LiDAR data from it.

10. a computer-implemented method for the LiDAR data point that identification is associated with the independent trees in forest, comprising:

Receive one group of LiDAR data point about area-of-interest;

The height of the each LiDAR data point based in described group is classified described LiDAR data point;

Be defined for each the confining surface in the described LiDAR data point in described group; And

One group of LiDAR data point with overlapping confining surface is defined as and represents independent trees.

11. computer-implemented methods according to claim 10, wherein, described confining surface limits by spheroid.

12. computer-implemented methods according to claim 10, wherein, described confining surface limits by spheroid.

13. computer-implemented methods according to claim 10, wherein, described confining surface limits by cone.

14. computer-implemented methods according to claim 10, wherein, described confining surface limits by cylinder.

15. 1 kinds of non-volatile computer readable medias, described non-volatile computer readable media stores instruction thereon, described instruction can be carried out to identify the LiDAR data point being associated with vegetation item by computing machine, and wherein, described instruction causes processor to carry out:

Receive one group of LiDAR data point about area-of-interest;

Analyze each in the LiDAR data point in described group to determine whether LiDAR data point has the position in the confining surface that one or more other LiDAR data points in for described group limit; With

If so, described LiDAR data point is added to the previously defined LiDAR group of data points being associated with vegetation item; And

If not, limit the new LiDAR group of data points being associated with new vegetation item.

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